Summary: Behavioral data is central to biomedical research, including both synchronous measures (e.g. brain activation and button-presses from a reading task in an fMRI scan), and those performed independently (e.g. a literacy questionnaire.) Compared to neurophysiology and brain imaging data, behavioral data is often relatively small, with file sizes in the megabytes rather than terabytes for both experimental scripts and resulting datasets. The key challenge for behavioral data is not size but variability: many studies are not designed with FAIR (Findable, Accessible, Interoperable, and Reusable) sharing or automated analysis pipelines in mind. Those that are machine-readable lack common standards of format, organization, or documentation across labs or even individual studies. We propose to implement a standard for human behavioral experiments in the BRAIN initiative using a community-developed data specification, Psych-DS. Because Psych-DS is designed to be similar to the raw data researchers already acquire, this work will result in a broad pool of users adopting the standard without additional effort or interruption to existing workflows; feedback from these researchers will be central to development of all three aims of the proposal: First, we will create validator software for Psych-DS datasets, to ensure that tools implementing the standard remain cross-compatible for researchers using a variety of languages (Python, R, Javascript) as well as compiling datasets by hand. Second, the standard and validation packages will be integrated into at least three popular experiment presentation packages in wide use by psychologists and cognitive neuroscientists (jsPsych, PsychoPy, and Lookit/Children Helping Science). Third, to support projects that involve coordinated behavioral and neuroimaging/neurophysiological data, we will implement tools to translate between Psych-DS and the Brain Imaging Data Standard (BIDS). The lack of consensus around how behavioral data are organized prevents a broad and diverse swath of biomedically relevant research from being fully integrated with the infrastructures currently being built to support neuroscientific research at scale. Implementation and adoption of the Psych-DS standard will provide a machine-readable data format that can be used across a wide variety of research contexts, and lay the groundwork for further improvements to standardization and reproducibility in the biomedical and behavioral sciences.

Narrative/Public Health Statement: This proposal introduces a system for organizing scientific data, Psych-DS, which is designed to help scientists that work with all kinds of behavioral data, which is often collected or annotated by hand and stored in study- specific formats that are hard for another researcher to use or understand. Psych-DS turns common recommendations for good project organization (such as naming systems that are easy for both people and computers to understand) into a validator that can check whether scientists from different labs are following the rules in the same way. We propose to build this validator and then help several communities of scientists begin to use it, by providing Psych-DS data downloads and other tools that use the common format to support brain research that involves synchronizing behavioral data and neural measurements.